Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Archana Sapkota"'
Autor:
Terrance E. Boult, Archana Sapkota
Publikováno v:
BTAS
This paper addresses large scale, unconstrained, open set face recognition, which exhibits the properties of operational face recognition scenarios. Most of the existing face recognition databases have been designed under controlled conditions or hav
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a064adc3143dfff245d5e379c85bbc75
https://doi.org/10.1109/btas.2013.6712756
https://doi.org/10.1109/btas.2013.6712756
Publikováno v:
BTAS
While modern research in face recognition has focused on new feature representations, alternate learning methods for fusion of features, most have ignored the issue of unmodeled correlations in face data when combining diverse features such as simila
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2b175a79424bc249566cb05648d65693
https://doi.org/10.1109/btas.2013.6712723
https://doi.org/10.1109/btas.2013.6712723
Autor:
Archana Sapkota, Terrance E. Boult
Publikováno v:
EURASIP Journal on Image and Video Processing. 2013
Scale is one of the major challenges in recognition problems. For example, a face captured across large distances is considerably harder to recognize than the same face at small distances. Local binary pattern (LBP) and its variants have been success
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee6593a8625e6081b4ceb17c5303ba0a
https://doi.org/10.1186/1687-5281-2013-35
https://doi.org/10.1186/1687-5281-2013-35
Publikováno v:
IEEE transactions on pattern analysis and machine intelligence. 35(7)
To date, almost all experimental evaluations of machine learning-based recognition algorithms in computer vision have taken the form of “closed set” recognition, whereby all testing classes are known at training time. A more realistic scenario fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f5ff08361ed5c91ca8029b0abdebced
https://pubmed.ncbi.nlm.nih.gov/23682001
https://pubmed.ncbi.nlm.nih.gov/23682001
Autor:
Terrance E. Boult, Archana Sapkota
Publikováno v:
ICB
Multiple research has shown the advantage of patch-based or local representation for face recognition. This paper builds on a novel way of putting the patches in context, using a foveated representation. While humans focus on local regions and move b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3390a3a4b3faa2411c526c4a92ce6369
https://doi.org/10.1109/icb.2012.6199759
https://doi.org/10.1109/icb.2012.6199759
Publikováno v:
CVPR Workshops
Face recognition in unconstrained environments is one of the most challenging problems in biometrics. One vexing problem in unconstrained environments is that of scale; a face captured at large distances is considerably harder to recognize than the s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f118033dae98b47ee03e9328fdf81f7d
https://doi.org/10.1109/cvprw.2010.5544597
https://doi.org/10.1109/cvprw.2010.5544597